Fast and accurate remote sensing image retrieval from large data archives has been an
important research topic in the remote sensing research literature. Recently, hashing-based …

In a data stream, concept drift refers to unpredictable distribution changes over time, which
violates the identical-distribution assumption required by conventional machine learning …

In this paper, we present a novel deep metric learning method to tackle the multi-label image
classification problem. In order to better learn the correlations among images features, as …

Current models and algorithms have been increasingly required to learn in a nonstationary
environment because the phenomenon of concept drift (or pattern shift) may occur, that is …

Typically in practical applications, the learning performance of a model is inclined to be
jeopardized by the inadequacy of labeled instances and the unbalance within various …

Blur artifacts can seriously degrade the visual quality of images, and numerous deblurring
methods have been proposed for specific scenarios. However, in most real-world images …

Direct regression and anchor are the two mainly effective and prevailing mechanisms in the
paradigm of scene text detection. However, the use of direct regression-based methods may …

With the continuous generation of huge volumes of streaming data, streaming data
regression has become more complicated. A regressor that predicts two or more outputs, ie …

Visual Question Answering (VQA) serves as a proxy for evaluating the scene understanding
of an intelligent agent by answering questions about images. Most VQA benchmarks to date …

Unmanned aerial vehicles (UAV's) safe flight is one of the most important tasks of ground
control stations (GCS). However, sometimes due to communication failure between ground …